The present invention generally relates to imaging system calibration. In particular, the present invention relates to object positioning and calibration of an imaging system.
Medical diagnostic imaging systems encompass a variety of imaging modalities, such as x-ray systems, computerized tomography (CT) systems, ultrasound systems, electron beam tomography (EBT) systems, magnetic resonance (MR) systems, and the like. Medical diagnostic imaging systems generate images of an object, such as a patient, for example, through exposure to an energy source, such as x-rays passing through a patient, for example. The generated images may be used for many purposes. For instance, internal defects in an object may be detected. Additionally, changes in internal structure or alignment may be determined. Fluid flow within an object may also be represented. Furthermore, the image may show the presence or absence of objects in an object. The information gained from medical diagnostic imaging has applications in many fields, including medicine and manufacturing.
In order to help ensure that medical diagnostic images are reliable, it is advantageous to calibrate medical diagnostic imaging systems. The calibration of imaging systems is important for several reasons, including image quality, measurement accuracy and system performance. Poor image calibration may prevent reliable analysis of an image. The calibration of medical imaging systems may help to produce a distinct and usable representation of an object.
Inaccuracies in an imaging system may result in blurring, streaking, or introduction of ghost images or artifacts in the resulting image. For example, if a detector position or the center of a medical imaging system is inaccurate, an x-ray will be projected at an incorrect angle and produce an error in the resulting image. Thus, a need exists for a method and apparatus for more accurate calibration of a medical diagnostic imaging system.
In a cathlab, for example, a physician needs fast and accurate angiographic methods in order to minimize the time spent on determining quantitative information. Traditional quantification procedures are often unsatisfactory because they require using a well-known object as reference (for example, a catheter or calibration sphere) for each frame to calibrate. These steps are time consuming and not do carry clinical value. Even if catheter calibration has eased the procedure, accuracy and precision constraints have to be considered with care. Indeed, an error of percentage in the catheter size, which may be due to the catheter manufacturer, corresponds to an equivalent error in the vessel size for vessel quantification. Current calibration methods may be automatic except for entering the height of the element of interest above the table, which is not a priori known.
The growth of interventional procedures drives the development of simple, fast and accurate quantification methods. Quantification is used to assess the volume of a left ventricle, for example, but also for choosing the size of a stent or a balloon during the course of a revascularization procedure. However, in numerous occasions, the therapeutic procedures are executed within the same session as the diagnosis, and the physician seeks to minimize the time spent on determining quantitative information such as the diseased artery reference diameter or the lesion length.
In most cases in the cathlab, a vessel dimension is computed by multiplying its apparent size in the image by a calibration factor expressed in millimeters per pixel. Usually, this calibration factor is determined by considering the apparent size of a reference object of known size. Generally, the reference object is the catheter. This method requires a user to perform operations not directly related to the clinical objective, such as obtaining an image frame including the catheter, either edge detecting or depositing one or two points on the catheter, and entering the size of the catheter. In addition, accuracy and precision constraints have to be taken into account. The size of the catheter has to be known very precisely. An error of 5% in this parameter corresponds to an error of the same magnitude in the vessel size, for example. The catheter and the vessel under analysis have to be in a plane parallel to the image plane.
Several recent imaging systems, such as the GE Innova, Advantage Workstation, and CA1000, have introduced or will introduce an auto calibration feature to improve the effectiveness of image analysis due to an increase in efficiency of operation. An efficiency increase is achieved by provide user access to a system calibration without having to stop an imaging workflow, obtain an image, and then measure a separate target for calibration. Currently, however, the auto calibration feature requires an input variable representing a height of a proposed body part above a positioning table (effectively, the distance away from the geometric “isocenter” of the x-ray beam). The height input variable is either accepted as a default value or is input by the user. Since the tabletop distance is recorded in the image data, the height is correlated with the isocenter distance). This means the auto calibration has either a manual step that makes the system un-necessarily slower and/or a default value that has some inaccuracy potential. Additionally, current methods of calibration do not account for differences in patient body type, with corresponding differences in position for an object to be imaged.
Therefore, a need exists for systems and methods for calibration of an image acquisition system. A need exists for systems and methods for improved auto-calibration of an image acquisition system. Furthermore, a need exists for systems and methods for calibration based on organs, as well as catheters and blood vessels, to be imaged. Systems and methods accommodating a variety of patient body types and objects to be imaged would be highly desirable.